What is TFM
FMC/TFM defines a family of processes and TPAC offers most of them. This page shows will provide explanation and show the benefits of the different types of TFM imaging that are currently available.
TFM (Total Focusing Method) is a signal processing algorithm applied on the raw RF waveform data from performing FMC (Full Matrix Capture). The TFM algorithm is used to recreate focus on every point of the reconstructed image.
Now with the speed of modern computing, we can use TFM for real time imaging. The image below shows a comparison between TFM and conventional phased array UT. The diagram represents the standard TFM implementation.
Uses different waves from generic TFM, possibly different frequencies, this technique allows high speed, low data file size, excellent SNR, and in the range of 20 to 30 dB more sensitivity than Generic TFM.
Typically more than 20 frame per sec.
Adaptive method applied on TFM or AFM
TFM or AFM method that allows correction of the geometry irregularities without knowing the profile of the surface or the back wall. The FMC data provides all necessary information to correct the TFM or AFM processing in real time.
TFM method based on the inverse problem that works with iterations, and gives improvement of the resolution from 1/10th to 1/20th of a wavelength. An image is processed in a few seconds.
Adaptive method on TFMp
Comparison of Different TFM Types
Below are a few different examples of types of TFM. There are many more types available. TPAC offers most TFM types available on the market.
This recent, popular technique offers similar resolution to SAFT, but with a very good SNR. Generic TFM can be implemented in hardware or in software. The amount of data is very high and the speed is limited.
Typically less than 10 frames per sec.
This is an old technique from before phased array was technologically feasible, but can be applied to phased array. Fast, the resolution is excellent, but the SNR is very poor. Typically more than 20 frames per sec.
Migration is a TFM process that can be applied to any FMC data where the probe is flat and parallel to the surface. Provides better contrast and resolution than generic TFM. Real time.
AFM is a TFM process that works using different waves from cylindrical as well as multi-frame FMC-like process.
The actual reduction of data and increased sensitivity by a factor of more than 10dB makes it very useful for most applications.